Ansible Automation Setup for Web Servers

Note: as your site grows, manually configuring each server becomes unviable. Differing config files, forgotten dependencies, production errors — all slow down development and increase incident risk. At TrueTech we've been using Ansible (Wikipedia) for server automation for over 5 years. Our experience shows: properly structured playbooks cut deployment time by 5x and reduce errors by 90%. Unlike scripts, Ansible guarantees every environment — from dev to production — is configured identically. We've automated over 50 servers — configuration errors dropped to zero, and provisioning a new server takes 15 minutes instead of 3 hours.

Ansible is more than just another tool; it's an Infrastructure as Code approach. It describes the desired system state in declarative YAML playbooks, eliminating human error. For Laravel projects with frequent releases and migrations, this is especially critical: a single config mismatch can cause downtime. Want to discuss automation for your project? Request a free consultation.

Ansible Setup: Key Points

Ansible works over SSH, requiring no agents on target machines. Key features:

• Idempotence: repeated runs don't alter correct configuration.
• Simplicity: nothing but Python and SSH, no agents.
• Modularity: roles allow code reuse across projects.

These properties are critical for Laravel projects with frequent updates and migrations. Compare with manual management:

Comparison with other tools:

What specific problems does Ansible solve?

Ansible solves three key issues: environment inconsistency, slow deployment, and human errors. Dev, staging, and production are now configured identically using a single playbook. Deployment takes minutes instead of hours thanks to automated git pull and composer install on each server. Human errors are eliminated: Ansible checks every state and can roll back changes on failure.

How does Ansible speed up deployment?

Using roles and playbooks, we automate the full deployment cycle: from server setup to application deployment with minimal downtime. Below is an example project structure for Laravel + Nginx.

Example Project Structure and Playbooks

For a real Laravel + Nginx project, we use this hierarchy:

ansible/
├── inventory/
│   ├── production
│   └── staging
├── group_vars/
│   ├── all.yml
│   └── webservers.yml
├── host_vars/
│   └── web01.yml
├── roles/
│   ├── common/
│   ├── nginx/
│   ├── php/
│   └── myapp/
├── playbooks/
│   ├── setup.yml
│   └── deploy.yml
└── ansible.cfg

Inventory and group_vars

[webservers]
web01 ansible_host=10.0.0.10
web02 ansible_host=10.0.0.11

[dbservers]
db01 ansible_host=10.0.0.20

[webservers:vars]
ansible_user=deploy
ansible_ssh_private_key_file=~/.ssh/id_rsa

Environment variables (e.g., PHP version 8.3) are placed in group_vars/all.yml, simplifying switching between environments.

Server setup playbook

- name: Setup web servers
  hosts: webservers
  become: true

  roles:
    - common
    - nginx
    - php
    - myapp

  vars:
    app_name: myapp
    app_domain: example.com
    php_version: "8.3"

Application deploy role

- name: Create deploy user
  ansible.builtin.user:
    name: deploy
    shell: /bin/bash
    groups: www-data
    append: yes

- name: Clone/update repository
  ansible.builtin.git:
    repo: "https://github.com/user/{{ app_name }}.git"
    dest: "/var/www/{{ app_name }}"
    version: "{{ app_branch | default('main') }}"
    force: yes
  become_user: deploy

- name: Install PHP dependencies
  community.general.composer:
    command: install
    working_dir: "/var/www/{{ app_name }}"
    no_dev: yes
    optimize_autoloader: yes
  become_user: deploy

- name: Copy .env file
  ansible.builtin.template:
    src: .env.j2
    dest: "/var/www/{{ app_name }}/.env"
    owner: deploy
    group: www-data
    mode: "0640"

- name: Run migrations
  ansible.builtin.command:
    cmd: php artisan migrate --force
    chdir: "/var/www/{{ app_name }}"
  become_user: deploy
  changed_when: false

- name: Clear caches
  ansible.builtin.command:
    cmd: "php artisan {{ item }}"
    chdir: "/var/www/{{ app_name }}"
  loop:
    - config:cache
    - route:cache
    - view:cache
  become_user: deploy
  changed_when: false

Deploy playbook with rolling update

- name: Deploy application
  hosts: webservers
  serial: 1
  become: true

  vars:
    app_branch: "{{ branch | default('main') }}"

  pre_tasks:
    - name: Enable maintenance mode
      ansible.builtin.command:
        cmd: php artisan down --refresh=15
        chdir: "/var/www/{{ app_name }}"

  roles:
    - myapp

  post_tasks:
    - name: Disable maintenance mode
      ansible.builtin.command:
        cmd: php artisan up
        chdir: "/var/www/{{ app_name }}"

This playbook processes hosts one by one: enables maintenance mode, applies the myapp role (updates code, dependencies, migrations), then disables the mode. Users experience no downtime, and if an error occurs, changes can be rolled back on the problematic host.

What's included in Ansible setup

We provide a complete package:

• Inventory — structured description of all servers and environments.
• Roles and playbooks — web server, PHP, database, queue, and deployment configuration.
• Secrets management — encryption via Ansible Vault.
• Documentation — all commands and processes for your team.
• Developer training — how to run playbooks and add new roles.
• Support — 30 days post-implementation.

Process and Timeline

1. Current infrastructure analysis (1 day).
2. Design role structure and variables (1–2 days).
3. Write and test playbooks (2–3 days).
4. Deploy to staging and production (1 day).
5. Hand over documentation and training (1 day).

Total time for a typical PHP project: 5 to 7 working days. Cost is calculated individually after infrastructure analysis. Order a consultation on server automation — we'll implement Ansible in a week. Contact us to discuss your project.

Why trust us with automation?

• 5+ years of Ansible experience in production.
• Over 30 successful server automation projects (Laravel, WordPress, React).
• Engineers focused on security and idempotence.
• We guarantee that after implementation you'll be able to deploy with a single command without downtime.

Ansible is 10x faster than Bash scripts when deploying on multiple servers, and practice confirms this. We'll assess your project in 1 day. Get a free consultation — automate the routine and focus on development.

We regularly encounter a situation: "The site is not opening" at 3 a.m. — and it turns out that the VPS disk is full because nginx logs haven't been rotated for six months. Or the server went down under load on the day of an advertising campaign launch because the shared hosting had a limit of 50 concurrent connections. Setting up hosting and deployment is not about "where it's cheaper" but about what happens when something goes wrong. Our team helps avoid such incidents by designing infrastructure that accounts for real load patterns.

When to choose Vercel and Netlify?

Vercel is built for Next.js — deploy in one push, preview deployments for every PR, automatic CDN, Edge Functions, ISR without configuration. For frontend projects and JAMstack, it's the optimal choice: no operational overhead, time-to-deploy measured in minutes.

Real limitations: Vercel Serverless Functions run in us-east-1 by default (latency for Europe +80–100ms), Function timeout 300 seconds on Pro, Bandwidth 1TB/month on Pro. For heavy backend, you need workers or a separate server.

Netlify is closer to static sites and Edge Functions based on Deno Deploy. Build minutes are the main limitation on the free tier.

Why is Docker the foundation of predictable deployment?

"It works on my machine" — classic. Docker solves this through environment containerization. But a bad Dockerfile creates new problems.

A typical mistake: copying everything into the image without .dockerignore, resulting in an 800MB image instead of 80MB. node_modules inside the image weighs as much. Correct approach: multi-stage build.

FROM node:20-alpine AS builder
WORKDIR /app
COPY package*.json ./
RUN npm ci --only=production
COPY . .
RUN npm run build

FROM node:20-alpine AS runner
WORKDIR /app
COPY --from=builder /app/.next ./.next
COPY --from=builder /app/node_modules ./node_modules
COPY --from=builder /app/package.json ./package.json
EXPOSE 3000
CMD ["npm", "start"]

Final image: 180MB instead of 1.2GB. CI build time is reduced due to layer caching — if package.json hasn't changed, the layer with npm ci is taken from cache.

Docker Compose for local development and simple production scenarios: application + PostgreSQL + Redis in one configuration. For production on a single server, it's a perfectly viable option if there's no requirement for horizontal scaling.

More about containerization — Wikipedia: Docker.

How to set up Nginx as a reverse proxy?

Nginx in front of the application is standard for VPS and dedicated servers. Main functions: SSL termination, gzip, static files, rate limiting, upstream load balancing.

A configuration often done incorrectly: worker_processes auto — number of processes equals CPU count. worker_connections 1024 — that's 1024 per worker process. With 4 CPUs and 1024 connections = 4096 concurrent connections. For a high-traffic site, you need worker_connections 4096 and set keepalive_timeout 65.

For static assets with hash in the filename:

location ~* \.(js|css|woff2|png|webp)$ {
    expires 1y;
    add_header Cache-Control "public, immutable";
}

immutable tells the browser: don't revalidate this file even on hard refresh. This only works correctly with content-hashed filenames (which Vite/webpack do by default). Documentation — Wikipedia: Nginx.

AWS: flexibility and complexity

EC2 + Auto Scaling Group — classic for horizontal scaling. AMI with pre-installed application, Launch Template, ASG with min/desired/max instances, Application Load Balancer. When CPU > 70% for 3 minutes — scale out, when CPU < 30% for 15 minutes — scale in. Health check via ALB removes unhealthy instances from rotation.

ECS Fargate — containers without managing EC2. Deploy a Docker image, specify CPU/memory (512 CPU units = 0.5 vCPU, from 512MB memory), Fargate launches it. More expensive than Lambda, but no cold start and no timeout limitations. Suitable for long-running processes, WebSocket servers, heavy workers.

RDS for PostgreSQL with Multi-AZ: automatic failover in 1–2 minutes when primary fails. Read Replicas for scaling reads. RDS Proxy for connection pooling — Lambda functions cannot hold long-term connections, the proxy buffers this.

Kubernetes: when it is justified

K8s adds significant operational complexity. Justified when: multiple teams deploy independent services, fine-grained resource allocation per service is needed, canary deployments and blue/green without downtime are required.

AWS EKS, GKE, or managed k8s from Hetzner (cheaper). Helm charts for standard services. Horizontal Pod Autoscaler based on CPU and custom metrics (RPS via Prometheus).

For most startups and medium-sized projects, Kubernetes is overkill. ECS or Fly.io provide 80% of the capabilities with 20% of the operational complexity.

Monitoring and alerting

A server without monitoring is waiting for an incident. Minimal stack: Prometheus + Grafana (or Grafana Cloud for managed), alerting on disk > 80%, memory > 85%, CPU > 90% over 5 minutes, error rate > 1%. Uptime via Better Uptime or Upptime (self-hosted).

Logs: Loki + Grafana or CloudWatch Logs Insights. Structured JSON logs (winston, pino) are mandatory — otherwise, log searching becomes a pain.

What is included in hosting setup

• Audit of current infrastructure and load profiling
• Selection of target architecture (VPS, AWS, serverless, Kubernetes)
• Setting up CI/CD pipeline (GitHub Actions, GitLab CI) with automatic deployment
• IaC via Terraform or Pulumi (infrastructure as code)
• Configuration of Nginx, SSL certificates, HTTP/2, brotli
• Monitoring and alerting (Prometheus + Grafana, PagerDuty)
• Documentation of runbooks and team training

Additionally, contact us if you need migration from current hosting or integration with external services.

Work process

1. Audit of current infrastructure (2–5 days)
2. Selection of target architecture with load and budget justification (1–3 days)
3. Setting up CI/CD pipeline (GitHub Actions, GitLab CI) (2–5 days)
4. IaC via Terraform or Pulumi (3–10 days)
5. Setting up monitoring and alerting (2–5 days)
6. Documentation of runbooks and team training (1–3 days)

Our experience — 7 years on the market, over 50 projects, guarantee of operability after deployment.

Timeline

• Basic deployment on VPS with Docker + Nginx + CI/CD: 1–2 weeks.
• Setting up AWS infrastructure with Auto Scaling, RDS, CDN: 3–6 weeks.
• Migration to EKS from scratch: 6–12 weeks.
• Setting up Vercel/Netlify for JAMstack: 3–5 days.

The cost is calculated individually depending on complexity and scope of work. Get a consultation — we'll evaluate your architecture in one day.